diff --git a/pytorch_lightning/core/lightning.py b/pytorch_lightning/core/lightning.py
index 66d067a5146b6..70cd5d847eadd 100644
--- a/pytorch_lightning/core/lightning.py
+++ b/pytorch_lightning/core/lightning.py
@@ -76,6 +76,7 @@ def __init__(self, *args, **kwargs):
         self._example_input_array = None
         self._datamodule = None
 
+    @torch.jit.ignore
     @property
     def example_input_array(self) -> Any:
         return self._example_input_array
@@ -84,6 +85,7 @@ def example_input_array(self) -> Any:
     def example_input_array(self, example: Any) -> None:
         self._example_input_array = example
 
+    @torch.jit.ignore
     @property
     def datamodule(self) -> Any:
         return self._datamodule
@@ -92,6 +94,7 @@ def datamodule(self) -> Any:
     def datamodule(self, datamodule: Any) -> None:
         self._datamodule = datamodule
 
+    @torch.jit.ignore
     @property
     def on_gpu(self):
         """
@@ -1720,6 +1723,7 @@ def to_onnx(self, file_path: str, input_sample: Optional[Tensor] = None, **kwarg
 
         torch.onnx.export(self, input_data, file_path, **kwargs)
 
+    @torch.jit.ignore
     @property
     def hparams(self) -> Union[AttributeDict, str]:
         if not hasattr(self, '_hparams'):
diff --git a/pytorch_lightning/utilities/device_dtype_mixin.py b/pytorch_lightning/utilities/device_dtype_mixin.py
index bea3df3e5ced9..1767e06f968f7 100644
--- a/pytorch_lightning/utilities/device_dtype_mixin.py
+++ b/pytorch_lightning/utilities/device_dtype_mixin.py
@@ -11,6 +11,7 @@ def __init__(self):
         self._dtype = torch.get_default_dtype()
         self._device = torch.device('cpu')
 
+    @torch.jit.ignore
     @property
     def dtype(self) -> Union[str, torch.dtype]:
         return self._dtype
@@ -20,6 +21,7 @@ def dtype(self, new_dtype: Union[str, torch.dtype]):
         # necessary to avoid infinite recursion
         raise RuntimeError('Cannot set the dtype explicitly. Please use module.to(new_dtype).')
 
+    @torch.jit.ignore
     @property
     def device(self) -> Union[str, torch.device]:
         return self._device